Search Results for author: Hao Lu

Found 21 papers, 10 papers with code

Represent, Compare, and Learn: A Similarity-Aware Framework for Class-Agnostic Counting

no code implementations16 Mar 2022 Min Shi, Hao Lu, Chen Feng, Chengxin Liu, Zhiguo Cao

In this work, we propose a similarity-aware CAC framework that jointly learns representation and similarity metric.

Composing Photos Like a Photographer

1 code implementation CVPR 2021 Chaoyi Hong, Shuaiyuan Du, Ke Xian, Hao Lu, Zhiguo Cao, Weicai Zhong

To this end, we introduce the concept of the key composition map (KCM) to encode the composition rules.

Image Cropping

Dual-GAN: Joint BVP and Noise Modeling for Remote Physiological Measurement

no code implementations CVPR 2021 Hao Lu, Hu Han, S. Kevin Zhou

Remote photoplethysmography (rPPG) based physiological measurement has great application values in health monitoring, emotion analysis, etc.

Disentanglement Emotion Recognition +1

Bootstrapping Fitted Q-Evaluation for Off-Policy Inference

no code implementations6 Feb 2021 Botao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvári, Mengdi Wang

Bootstrapping provides a flexible and effective approach for assessing the quality of batch reinforcement learning, yet its theoretical property is less understood.

reinforcement-learning

TransView: Inside, Outside, and Across the Cropping View Boundaries

no code implementations ICCV 2021 Zhiyu Pan, Zhiguo Cao, Kewei Wang, Hao Lu, Weicai Zhong

We show that relation modeling between visual elements matters in cropping view recommendation.

Learning Affinity-Aware Upsampling for Deep Image Matting

1 code implementation CVPR 2021 Yutong Dai, Hao Lu, Chunhua Shen

By looking at existing upsampling operators from a unified mathematical perspective, we generalize them into a second-order form and introduce Affinity-Aware Upsampling (A2U) where upsampling kernels are generated using a light-weight lowrank bilinear model and are conditioned on second-order features.

14 Image Matting +1

The Effect of Dipole from $γ$-AgI Substrates on Heterogeneous Ice Nucleation

no code implementations23 Aug 2020 Hao Lu, Quanming Xu, Chaohong Wang, Jianyang Wu, Rongdun Hong, Xiang-Yang Liu, Zhisen Zhang

Heterogeneous ice nucleation is one of the most common and important process in the physical environment.

Materials Science

Weighing Counts: Sequential Crowd Counting by Reinforcement Learning

1 code implementation ECCV 2020 Liang Liu, Hao Lu, Hongwei Zou, Haipeng Xiong, Zhiguo Cao, Chunhua Shen

Inspired by scale weighing, we propose a novel 'counting scale' termed LibraNet where the count value is analogized by weight.

Crowd Counting reinforcement-learning

A Learning-based Iterative Method for Solving Vehicle Routing Problems

1 code implementation ICLR 2020 Hao Lu, Xingwen Zhang, Shuang Yang

This paper is concerned with solving combinatorial optimization problems, in particular, the capacitated vehicle routing problems (CVRP).

Combinatorial Optimization

From Open Set to Closed Set: Supervised Spatial Divide-and-Conquer for Object Counting

3 code implementations7 Jan 2020 Haipeng Xiong, Hao Lu, Chengxin Liu, Liang Liu, Chunhua Shen, Zhiguo Cao

Visual counting, a task that aims to estimate the number of objects from an image/video, is an open-set problem by nature, i. e., the number of population can vary in [0, inf) in theory.

Object Counting

Index Network

1 code implementation11 Aug 2019 Hao Lu, Yutong Dai, Chunhua Shen, Songcen Xu

By viewing the indices as a function of the feature map, we introduce the concept of "learning to index", and present a novel index-guided encoder-decoder framework where indices are self-learned adaptively from data and are used to guide the downsampling and upsampling stages, without extra training supervision.

Grayscale Image Denoising Image Denoising +3

Deep attention-based classification network for robust depth prediction

1 code implementation11 Jul 2018 Ruibo Li, Ke Xian, Chunhua Shen, Zhiguo Cao, Hao Lu, Lingxiao Hang

However, robust depth prediction suffers from two challenging problems: a) How to extract more discriminative features for different scenes (compared to a single scene)?

Classification Deep Attention +4

The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference

no code implementations ICML 2018 Hao Lu, Yuan Cao, Zhuoran Yang, Junwei Lu, Han Liu, Zhaoran Wang

We study the hypothesis testing problem of inferring the existence of combinatorial structures in undirected graphical models.

Two-sample testing

When Unsupervised Domain Adaptation Meets Tensor Representations

1 code implementation ICCV 2017 Hao Lu, Lei Zhang, Zhiguo Cao, Wei Wei, Ke Xian, Chunhua Shen, Anton Van Den Hengel

Domain adaption (DA) allows machine learning methods trained on data sampled from one distribution to be applied to data sampled from another.

Unsupervised Domain Adaptation

TasselNet: Counting maize tassels in the wild via local counts regression network

no code implementations7 Jul 2017 Hao Lu, Zhiguo Cao, Yang Xiao, Bohan Zhuang, Chunhua Shen

To our knowledge, this is the first time that a plant-related counting problem is considered using computer vision technologies under unconstrained field-based environment.

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